ArticleBioinformatics (Oxford, England)2020
How to get your goat: automated identification of species from MALDI-ToF spectra.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Chemometric analysis of ethoxylated polymer products using extracted MALDI-TOF-MS peak distribution features.PloS one · 2025Article
- Clothomics: a practical guide to understand the opportunities and challenges of omics-based methods in archaeological cloth research.NPJ heritage science · 2025Review
- SpecieScan: semi-automated taxonomic identification of bone collagen peptides from MALDI-ToF-MS.Bioinformatics (Oxford, England) · 2024Article
- Artefact Profiling: Panomics Approaches for Understanding the Materiality of Written Artefacts.Molecules (Basel, Switzerland) · 2023Review
- A biological reading of a palimpsest.iScience · 2023Article
- Paleoproteomics.Chemical reviews · 2022Review
- Review
- A primer for ZooMS applications in archaeology.Proceedings of the National Academy of Sciences of the United States of America · 2022Review
- A biocodicological analysis of the medieval library and archive from Orval Abbey, Belgium.Royal Society open science · 2021Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
motivationClassification of archaeological animal samples is commonly achieved via manual examination of matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) spectra. This is a time-consuming process which requires significant training and which does not produce a measure of confidence in the classification. We present a new, automated method for arriving at a classification of a MALDI-ToF sample, provided the collagen sequences for each candidate species are available. The approach derives a set of peptide masses from the sequence data for comparison with the sample data, which is carried out by cross-correlation. A novel way of combining evidence from multiple marker peptides is used to interpret the raw alignments and arrive at a classification with an associated confidence measure.
resultsTo illustrate the efficacy of the approach, we tested the new method with a previously published classification of parchment folia from a copy of the Gospel of Luke, produced around 1120 C.E. by scribes at St Augustine's Abbey in Canterbury, UK. In total, 80 of the 81 samples were given identical classifications by both methods. In addition, the new method gives a quantifiable level of confidence in each classification. AVAILABILITY AND IMPLEMENTATION: The software can be found at https://github.com/bioarch-sjh/bacollite, and can be installed in R using devtools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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